Revisions to Having problems with NonlinearModelFit

deleted 1 character in body

edited Feb 26, 2017 at 13:59

108.6k
16
107
263

I have data points — denoted by Fk— covering quite a large range $(1,\,10^{1010})$. I plotted them with ListLogPlot. Then I tried to fit the data points using NonlinearModelFit, and now I have two problems:

Fitting the data points
```
 fit = NonlinearModelFit[Fk[300], a*k^(B*k), {a, B}, k] 
```
gives 1 k^1 for the fitted model.

However, fitting the data points with:
```
 fit2 = NonlinearModelFit[Fk[300], a*k^(b*c*k), {a, b, c}, k] 
```
gives the fitted model 140.714 k^1.16997 k which I completely do not unterstand. I mean why should the output change upon inserting the variable $c$, which could also be combined with $b$ such that say $b\,c= B$ and fit should be equal to fit2.
If I now plot the data $F_k$Fk vs. $k$k together with the fitted model, the fitted curve ends at some value of $k \approx 120$, and I do not unterstand why. My code for this is
```
 Show[{ListLogPlot[Fk[300], PlotStyle -> Red], LogPlot[fit2[k], {k, 0, 300}]}] 
```

Red dots = data points; blue line = fitted curve

I have data points — denoted by Fk— covering quite a large range $(1,\,10^{1010})$. I plotted them with ListLogPlot. Then I tried to fit the data points using NonlinearModelFit, and now I have two problems:

Fitting the data points
```
 fit = NonlinearModelFit[Fk[300], a*k^(B*k), {a, B}, k] 
```
gives 1 k^1 for the fitted model.

However, fitting the data points with:
```
 fit2 = NonlinearModelFit[Fk[300], a*k^(b*c*k), {a, b, c}, k] 
```
gives the fitted model 140.714 k^1.16997 k which I completely do not unterstand. I mean why should the output change upon inserting the variable $c$, which could also be combined with $b$ such that say $b\,c= B$ and fit should be equal to fit2.
If I now plot the data $F_k$ vs. $k$ together with the fitted model, the fitted curve ends at some value of $k \approx 120$, and I do not unterstand why. My code for this is
```
 Show[{ListLogPlot[Fk[300], PlotStyle -> Red], LogPlot[fit2[k], {k, 0, 300}]}] 
```

Red dots = data points; blue line = fitted curve

I have data points — denoted by Fk— covering quite a large range $(1,\,10^{1010})$. I plotted them with ListLogPlot. Then I tried to fit the data points using NonlinearModelFit, and now I have two problems:

Fitting the data points
```
 fit = NonlinearModelFit[Fk[300], a*k^(B*k), {a, B}, k] 
```
gives 1 k^1 for the fitted model.

However, fitting the data points with:
```
 fit2 = NonlinearModelFit[Fk[300], a*k^(b*c*k), {a, b, c}, k] 
```
gives the fitted model 140.714 k^1.16997 k which I completely do not unterstand. I mean why should the output change upon inserting the variable $c$, which could also be combined with $b$ such that say $b\,c= B$ and fit should be equal to fit2.
If I now plot the data Fk vs. k together with the fitted model, the fitted curve ends at some value of $k \approx 120$, and I do not unterstand why. My code for this is
```
 Show[{ListLogPlot[Fk[300], PlotStyle -> Red], LogPlot[fit2[k], {k, 0, 300}]}] 
```

Red dots = data points; blue line = fitted curve

deleted 14 characters in body

Source Link

edited Feb 26, 2017 at 13:04

m_goldberg

108.6k
16
107
263

I have data points — denoted in the Plot by $F_k$ —Fk— covering quite a large range $(1,\,10^{1010})$. I plotted them with ListLogPlot. Then I tried to fit the data points using NonlinearModelFit, and now I have two problems:

Fitting the data points
```
 fit = NonlinearModelFit[Fk[300], a*k^(B*k), {a, B}, k] 
```
gives 1 k^1 for the fitted model.

However, fitting the data points with:
```
 fit2 = NonlinearModelFit[Fk[300], a*k^(b*c*k), {a, b, c}, k] 
```
gives the fitted model 140.714 k^1.16997 k which I completely do not unterstand. I mean why should the output change upon inserting the variable $c$, which could also be combined with $b$ such that say $b\,c= B$ and fit should be equal to fit2.
If I now plot the data $F_k$ vs. $k$ together with the fitted model, the fitted curve ends at some value of $k \approx 120$, and I do not unterstand why. My code for this is
```
 Show[{ListLogPlot[Fk[300], PlotStyle -> Red], LogPlot[fit2[k], {k, 0, 300}]}] 
```

Red dots = data points; blue line = fitted curve

I have data points — denoted in the Plot by $F_k$ — covering quite a large range $(1,\,10^{1010})$. I plotted them with ListLogPlot. Then I tried to fit the data points using NonlinearModelFit, and now I have two problems:

Fitting the data points
```
 fit = NonlinearModelFit[Fk[300], a*k^(B*k), {a, B}, k] 
```
gives 1 k^1 for the fitted model.

However, fitting the data points with:
```
 fit2 = NonlinearModelFit[Fk[300], a*k^(b*c*k), {a, b, c}, k] 
```
gives the fitted model 140.714 k^1.16997 k which I completely do not unterstand. I mean why should the output change upon inserting the variable $c$, which could also be combined with $b$ such that say $b\,c= B$ and fit should be equal to fit2.
If I now plot the data $F_k$ vs. $k$ together with the fitted model, the fitted curve ends at some value of $k \approx 120$, and I do not unterstand why. My code for this is
```
 Show[{ListLogPlot[Fk[300], PlotStyle -> Red], LogPlot[fit2[k], {k, 0, 300}]}] 
```

Red dots = data points; blue line = fitted curve

I have data points — denoted by Fk— covering quite a large range $(1,\,10^{1010})$. I plotted them with ListLogPlot. Then I tried to fit the data points using NonlinearModelFit, and now I have two problems:

Fitting the data points
```
 fit = NonlinearModelFit[Fk[300], a*k^(B*k), {a, B}, k] 
```
gives 1 k^1 for the fitted model.

However, fitting the data points with:
```
 fit2 = NonlinearModelFit[Fk[300], a*k^(b*c*k), {a, b, c}, k] 
```
gives the fitted model 140.714 k^1.16997 k which I completely do not unterstand. I mean why should the output change upon inserting the variable $c$, which could also be combined with $b$ such that say $b\,c= B$ and fit should be equal to fit2.
If I now plot the data $F_k$ vs. $k$ together with the fitted model, the fitted curve ends at some value of $k \approx 120$, and I do not unterstand why. My code for this is
```
 Show[{ListLogPlot[Fk[300], PlotStyle -> Red], LogPlot[fit2[k], {k, 0, 300}]}] 
```

Red dots = data points; blue line = fitted curve

added 1 character in body

Source Link

edited Feb 26, 2017 at 13:00

user46908

11
2

I have data points — denoted in the Plot by $F_k$ — covering quite a large range $(1,\,10^{1010})$. I plotted them with ListLogPlot. Then I tried to fit the data points using NonlinearModelFit, and now I have two problems:

Fitting the data points
```
 fit = NonlinearModelFit[Fk[300], k^Bka*k^(B*k), {a, B}, k] 
```
gives 1 k^1 for the fitted model.

However, fitting the data points with:
```
 fit2 = NonlinearModelFit[Fk[300], ak^a*k^(b c kb*c*k), {a, b, c}, k] 
```
gives the fitted model 140.714 k^1.16997 k which I completely do not unterstand. I mean why should the output change upon inserting the variable $c$, which could also be combined with $b$ such that say $b\,c= B$ and fit should be equal to fit2.
If I now plot the data $F_k$ vs. $k$ together with the fitted model, the fitted curve ends at some value of $k \approx 120$, and I do not unterstand why. My code for this is
```
 Show[{ListLogPlot[Fk[300], PlotStyle -> Red], LogPlot[fit2[k], {k, 0, 300}]}] 
```

Red dots = data points; blue line = fitted curve

I have data points — denoted in the Plot by $F_k$ — covering quite a large range $(1,\,10^{1010})$. I plotted them with ListLogPlot. Then I tried to fit the data points using NonlinearModelFit, and now I have two problems:

Fitting the data points
```
 fit = NonlinearModelFit[Fk[300], k^Bk, {a, B}, k] 
```
gives 1 k^1 for the fitted model.

However, fitting the data points with:
```
 fit2 = NonlinearModelFit[Fk[300], ak^(b c k), {a, b, c}, k] 
```
gives the fitted model 140.714 k^1.16997 k which I completely do not unterstand. I mean why should the output change upon inserting the variable $c$, which could also be combined with $b$ such that say $b\,c= B$ and fit should be equal to fit2.
If I now plot the data $F_k$ vs. $k$ together with the fitted model, the fitted curve ends at some value of $k \approx 120$, and I do not unterstand why. My code for this is
```
 Show[{ListLogPlot[Fk[300], PlotStyle -> Red], LogPlot[fit2[k], {k, 0, 300}]}] 
```

Red dots = data points; blue line = fitted curve

I have data points — denoted in the Plot by $F_k$ — covering quite a large range $(1,\,10^{1010})$. I plotted them with ListLogPlot. Then I tried to fit the data points using NonlinearModelFit, and now I have two problems:

Fitting the data points
```
 fit = NonlinearModelFit[Fk[300], a*k^(B*k), {a, B}, k] 
```
gives 1 k^1 for the fitted model.

However, fitting the data points with:
```
 fit2 = NonlinearModelFit[Fk[300], a*k^(b*c*k), {a, b, c}, k] 
```
gives the fitted model 140.714 k^1.16997 k which I completely do not unterstand. I mean why should the output change upon inserting the variable $c$, which could also be combined with $b$ such that say $b\,c= B$ and fit should be equal to fit2.
If I now plot the data $F_k$ vs. $k$ together with the fitted model, the fitted curve ends at some value of $k \approx 120$, and I do not unterstand why. My code for this is
```
 Show[{ListLogPlot[Fk[300], PlotStyle -> Red], LogPlot[fit2[k], {k, 0, 300}]}] 
```